MétaCan
Menu
Back to cohort
Record W3130450532 · doi:10.1017/jfm.2020.1166

Analytical solution of the Burnett equations for gaseous flow in a long microchannel

2021· article· en· W3130450532 on OpenAlexaff
Aishwarya Rath, Upendra Yadav, Amit Agrawal

Bibliographic record

VenueJournal of Fluid Mechanics · 2021
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of Alberta
FundersBoard of Research in Nuclear Sciences
KeywordsMicrochannelMomentum (technical analysis)Exact solutions in general relativityMechanicsDirect simulation Monte CarloPhysicsFlow (mathematics)Boundary value problemWork (physics)Differential equationClassical mechanicsMonte Carlo methodThermodynamicsMathematicsDynamic Monte Carlo method

Abstract

fetched live from OpenAlex

This paper presents an analytical solution of the Burnett equations for gaseous flow in a long microchannel. A non-dimensional analysis is first undertaken to reduce the governing equations into somewhat simplified differential equations, which are solved to obtain the pressure and velocity fields. The exact solution for pressure has been obtained by solving the cross-stream momentum equation, while the solution for velocity is obtained from the streamwise momentum equation. The required boundary conditions are obtained from the direct simulation Monte Carlo (DSMC) method. The obtained analytical solution is compared with the available DSMC and perturbation based solutions, and found to agree well. The work is particularly significant because analytical solutions of the Burnett equations are currently known in only a very few cases. The present analytical solution opens the possibility for further analysis by employing the expressions for pressure and velocity provided here.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score0.258

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.291
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Fluid MechanicsSame topicGas Dynamics and Kinetic TheoryFrench-language works237,207